Surface crack detection method and system

Abstract

The invention discloses a surface crack detection method and system, and relates to the technical field. The method comprises the following steps of collecting a crack image, wherein the crack image comprises a crossing point of a plurality of cracks and a calculation standard used for calculating actual length represented by each pixel point; extracting a plurality of local regions based on the crossing point, wherein each local region comprises a crack connected with the crossing point; and obtaining areas and perimeters of the cracks in the local regions to calculate average width of the cracks. The detection system comprises an image collection apparatus, an extraction module and a calculation module. According to the method and the system, the cracks are classified based on the crossing point of the cracks, each obtained local region comprises the crack connected with the crossing point, and the same calculation method is adopted for the local regions to obtain size data of the cracks, so that the crack classification repeatability is good, the calculation amount is reduced, and the calculation time and cost are shortened and reduced; and the method and the system are especially suitable for detection of complex surface cracks staggered and distributed irregularly.

Description

[0001] The invention relates to the field of crack detection, in particular to a detection method and system for surface cracks. Background technique [0002] There are inevitably cracks on the surface of buildings, highways, bridges and tunnels, such as cracks at the bottom of concrete bridges. Since cracks are one of the important factors affecting the safety of bridges, regular inspections of bridge structures are required to find out whether cracks occur and Extensions are an effective means of monitoring the condition of bridges. The traditional detection method is that the inspectors use a telescope to observe the cracks at the bottom of the bridge from a long distance, or observe the cracks at the bottom of the bridge at close range through the built bridge platform, and the inspectors manually record the length and width of the cracks and other data. Because the cracks at the bottom of the bridge are often staggered and distributed irregularly, the manual detection met...

AI Technical Summary

Problems solved by technology

However, for staggered and irregularly distributed cracks, the cracks in each local area are often different, and the statistical calculation based on each pixel in the crack area requires a large amount of calculation and takes a long time, resulting in low crack detection efficiency

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